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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Control of the forebody vortex orientation by asymmetric air injection. Part A: Application to enhance departure/spin recovery of fighter aircraft. Part B: Details of the flow structure

A novel concept which was developed to provide powerful directional control effectiveness for a fighter aircraft at high angles of attack, where more traditional controls have very limited capability is discussed. The concept utilizes the energy concentrated in the strong forebody vortices (which form on slender bodies at high relative incidence) by controlling the lateral orientation of the vortices with respect to the body. The present concept seeks to utilize the inherent sensitivity of the vortex positioning and its bistable nature to an advantage allowing control of the forces which are developed. As it turns out, the direction or sense of the asymmetric vortex pair is much easier to control than to attenuate. The work which was done to develop the concept for application to an aircraft is described and is directed toward the effects of the concept on aircraft forces and moments and on the flight mechanics of the aircraft during maneuvering at high angles of attack. The objective was to utilize the side force associated with asymmetric vortices, in a controlled manner, to enhance the ability of the fighter to recover from a departure from controlled flight. The results from these water tunnel and wind tunnel experiments show that a small amount of tangential blowing along the forebody near the apex can effectively alter the forebody vortex system and generate large restoring yawing moments.

Skow, A. M.↗
NASA NTRS1989

Efficient eigenvalue assignment for large space structures

A novel and efficient approach for the eigenvalue assignment of large first-order time-invariant systems is developed using full-state feedback and output feedback. First, a Schur decomposition is applied to triangularize the state matrix. Second, a series of coordinate rotations (Givens rotations) are used to move the eigenvalue to be reassigned to the end of the diagonal of its Schur form. Third, the eigenvalue is moved to the desired location by a full-state feedback, without affecting the remaining eigenvalues. The second and third step can be repeated until all the assignable eigenvalues are moved to the desired locations. Given the freedom of multiple inputs, the feedback gain matrix is calculated to minimize an objective function composed of a gain matrix norm and/or a robustness index of the closed-loop system. Numerical examples are given to demonstrate the feasibility of the proposed approach.

Maghami, Peiman G.↗
NASA NTRS1991

Integrated adaptive filtering and design for control experiments of flexible structures

A novel method is presented of identifying a state space model and a state estimator for linear stochastic systems from input and output data. The method is primarily based on the relations between the state space model and the finite difference model for linear stochastic systems derived through projection filters. It is proven that least squares identification of a finite difference model converges to the model derived from the projection filters. System pulse response samples are computed from the coefficients of the finite difference model. In estimating the corresponding state estimator gain, a z-domain method is used. First the deterministic component of the output is subtracted out, and then the state estimator gain is obtained by whitening the remaining signal. Experimental example is used to illustrate the feasibility of the method.

Huang, Jen-Kuang↗
DOE OSTI2025

Enhanced pool boiling heat transfer using novel inverted trapezoid microgroove structures

Pool boiling heat transfer improvements with enhanced surfaces have been extensively studied for various hydrofluorocarbon (HFC) refrigerants. However, there is a limited number of studies in the open literature that focus on the pool boiling heat transfer characteristics of hydrofluoroolefin (HFO) refrigerants on enhanced surfaces. This study aims to address this gap by analyzing the pool boiling behavior of HFO refrigerants, specifically R1234yf and R1234ze(E). Experiments were conducted on both plain surfaces and novel inverted trapezoid microgroove structures. Further, the experimental results indicate that the microgroove structures can improve heat transfer coefficients by up to 80% compared to plain surfaces. Additionally, the performance of R1234yf and R1234ze(E) was compared to that of R134. It was observed that R1234yf exhibited comparable performance to R134a, while R1234ze(E) showed slightly lower performance. To assess the influence of saturation temperature on pool boiling heat transfer, tests were conducted at different saturation temperatures of 15℃, 25℃, and 35℃. The findings revealed that the pool boiling heat transfer coefficient increases with rising saturation temperature.

42 ENGINEERING↗
DOE OSTI2025

Crystal structure of MutYX: a novel clusterless adenine DNA glycosylase with a distinct C-terminal domain and 8-oxoguanine recognition sphere

Abstract The [4Fe–4S] cluster is an important cofactor of the base excision repair (BER) adenine DNA glycosylase MutY to prevent mutations associated with 8-oxoguanine (OG). Several MutYs lacking the [4Fe–4S] cofactor have been identified. Phylogenetic analysis shows that clusterless MutYs are distributed in two clades suggesting cofactor loss has occurred in multiple independent evolutionary events. Herein, we determined the first crystal structure of a clusterless MutY complexed with DNA. On the basis of the dramatic structural divergence from canonical MutYs, we refer to this as representative of a clusterless MutY subgroup “MutYX.” Interestingly, MutYX compensates for the missing [4Fe–4S] cofactor to maintain positioning of catalytic residues by expanding a pre-existing α-helix and acquisition of a new α-helix. Surprisingly, MutYX also acquired a new C-terminal domain that uniquely recognizes OG using residues Gln201 and Arg209. Adenine glycosylase assays and binding affinity measurements indicate that Arg209 is the primary residue responsible for OG:A lesion specificity, while Gln201 assists by bridging OG and Arg209. Surprisingly, replacement of Arg209 and Gln201 with Ala increased activity toward G:A mismatches. The MutYX structure serves as an example of devolution, capturing structural features required to retain function in the absence of a metal cofactor considered indispensable.

Trasviña-Arenas, Carlos H [University of Californi↗
DOE OSTI2024

Structure-Based Identification of Novel Histone Deacetylase 4 (HDAC4) Inhibitors

Histone deacetylases (HDACs) are important cancer drug targets. Existing FDA-approved drugs target the catalytic pocket of HDACs, which is conserved across subfamilies (classes) of HDAC. However, engineering specificity is an important goal. Herein, we use molecular modeling approaches to identify and target potential novel pockets specific to Class IIA HDAC-HDAC4 at the interface between HDAC4 and the transcriptional corepressor component protein NCoR. These pockets were screened using an ensemble docking approach combined with consensus scoring to identify compounds with a different binding mechanism than the currently known HDAC modulators. Binding was compared in experimental assays between HDAC4 and HDAC3, which belong to a different family of HDACs. HDAC4 was significantly inhibited by compound 88402 but not HDAC3. Two other compounds (67436 and 134199) had IC50 values in the low micromolar range for both HDACs, which is comparable to the known inhibitor of HDAC4, SAHA (Vorinostat). However, both of these compounds were significantly weaker inhibitors of HDAC3 than SAHA and thus more selective, albeit to a limited extent. Five compounds exhibited activity on human breast carcinoma and/or urothelial carcinoma cell lines. The present result suggests potential mechanistic and chemical approaches for developing selective HDAC4 modulators.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

High-Resolution Tandem Mass Spectrometry-Based Analysis of Model Lignin–Iron Complexes: Novel Pipeline and Complex Structures

Understanding the chemical nature of soil organic carbon (SOC) with great potential to bind iron (Fe) minerals is critical for predicting the stability of SOC. Organic ligands of Fe are among the top candidates for SOCs able to strongly sorb on Fe minerals, but most of them are still molecularly uncharacterized. To shed insights into the chemical nature of organic ligands in soil and their fate, this study developed a protocol for identifying organic ligands using ultrahigh-performance liquid chromatography-high-resolution tandem mass spectrometry (UHPLC-HRMS/MS) and metabolomic tools. The protocol was used for investigating the Fe complexes formed by model compounds of lignin-derived organic ligands, namely, caffeic acid (CA), p-coumaric acid (CMA), vanillin (VNL), and cinnamic acid (CNA). Isotopologue analysis of 54/56 Fe was used to screen out the potential UHPLC-HRMS (m/z) features for complexes formed between organic ligands and Fe, with multiple features captured for CA, CMA, VNL, and CNA when 35/37 Cl isotopologue analysis was used as supplementary evidence for the complexes with Cl. MS/MS spectra, fragment analysis, and structure prediction with SIRIUS were used to annotate the structures of mono/bidentate mono/biligand complexes. The analysis determined the structures of monodentate and bidentate complexes of FeL x Cl y (L: organic ligand, x = 1–4, y = 0–3) formed by model compounds. The protocol developed in this study can be used to identify unknown organic ligands occurring in complex environmental samples and shed light on the molecular-level processes governing the stability of the SOC.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Modeling Effort of TriTruss Modular Structure for In-Space Assembled Telescope Foundational Structure

The TriTruss is a novel and innovative structural module developed by researchers at the NASA Langley Research Center to construct modular structures which can be assembled on-orbit for future persistent missions, including in-space assembled telescopes and platforms for science and communications. The TriTruss offers unique modular structural features including compact packaging for launch, the possibility of staged packaging, simple robotic deployment and assembly, and design versatility for specific space mission applications. This paper presents the modeling and analysis procedure for the TriTruss modular structure and the predicted frequency response of an In-Space Assembled Telescope’s (iSAT) primary reflector.

Structural Modeling↗
DOE OSTI2025

Transferable dispersion-aware machine learning interatomic potentials for multilayer transition metal dichalcogenide heterostructures

Stacking atomically thin transition metal dichalcogenides (TMDs) into heterostructures enables exploration of exotic quantum phases, particularly through twist-angle-controlled moiré superlattices. These structures exhibit novel electronic and optical behaviors driven by atomic-scale structural reconstruction. However, studying such systems with DFT is computationally demanding due to their large unit cells and van der Waals (vdW) interactions between layers. To address this, we develop a transferable neural network potential (NNP) that includes long-range vdW corrections up to 12Å with minimal overhead. Trained on vdW-corrected DFT data for Mo- and W-based TMDs with S, Se, and Te, the NNP accurately models monolayers, bilayers, heterostructures, and their interaction with h-BN substrates. It reproduces equilibrium structures, energy landscapes, phonon dispersions, and matches experimental atomic reconstructions in twisted WS2 and MoS2/WSe2 systems. We demonstrate that our NNP achieves DFT-level accuracy and high computational efficiency, enabling large-scale simulations of TMD-based moiré superlattices both with and without substrates.

materials for energy and catalysis↗
DOE OSTI2026

Structure preservation using discrete gradients in the Vlasov-Poisson-Landau system

We present a novel structure-preserving framework for solving the Vlasov-Poisson-Landau system of equations using a particle in cell (PIC) discretization combined with discrete gradient time integrators. The Vlasov-Poisson-Landau system is an accurate model for studying hot plasma dynamics at a kinetic scale where small-angle Coulomb collisions dominate. Our scheme guarantees conservation of mass, momentum and energy as well as preservation of the monotonicity of entropy production in both the time-continuous and discrete systems. We employ the conservative integrator for both the Hamiltonian Vlasov-Poisson equations and the dissipative Landau equation using the PETSc library (www.mcs.anl.gov/petsc) to showcase structure-preserving properties.

Discrete gradients↗
NASA NTRS2003

Growing Three-Dimensional Corneal Tissue in a Bioreactor

Spheroids of corneal tissue about 5 mm in diameter have been grown in a bioreactor from an in vitro culture of primary rabbit corneal cells to illustrate the production of optic cells from aggregates and tissue. In comparison with corneal tissues previously grown in vitro by other techniques, this tissue approximates intact corneal tissue more closely in both size and structure. This novel three-dimensional tissue can be used to model cell structures and functions in normal and abnormal corneas. Efforts continue to refine the present in vitro method into one for producing human corneal tissue to overcome the chronic shortage of donors for corneal transplants: The method would be used to prepare corneal tissues, either from in vitro cultures of a patient s own cells or from a well-defined culture from another human donor known to be healthy. As explained in several articles in prior issues of NASA Tech Briefs, generally cylindrical horizontal rotating bioreactors have been developed to provide nutrient-solution environments conducive to the 30 NASA Tech Briefs, October 2003 growth of delicate animal cells, with gentle, low-shear flow conditions that keep the cells in suspension without damaging them. The horizontal rotating bioreactor used in this method, denoted by the acronym "HARV," was described in "High-Aspect-Ratio Rotating Cell-Culture Vessel" (MSC-21662), NASA Tech Briefs, Vol. 16, No. 5 (May, 1992), page 150.

Spaulding, Glen F.↗
NASA NTRS1989

Novel photovoltaic delta-doped GaAs superlattice structure

An asymmetric delta-doped GaAs structure is described which exhibits novel photovoltaic effects and low-intensity nonlinear optics. Of particular interest in this kind of structure is the ability to design the electrooptical and nonlinear optical properties and the material response time over a wide range by appropriate design of the doping profile.

Glass, A. M.↗
DOE OSTI2024

Molecular Vision - Multimodal, multitask retrieval of molecular structure from measured signatures for reference-free compound identification

We are currently at risk of generating false conclusions based on limited methods to identify small molecules in biological systems and in chemical forensics. By definition, the chemical structures of novel small molecules have not been determined, let alone measured or synthesized. Currently, unambiguous structure determination of small molecules is constrained by the time and effort needed to isolate compounds and perform de novo structure elucidation using laboratory-based methods, significantly extending the time to inform mitigation strategies. To address this gap, we have developed a deep learning approach to directly map molecular structure to experimental signatures. We aim to unify measurement technologies employed in untargeted small molecule identification studies—such as infrared (IR) spectrometry, tandem mass spectrometry (MS/MS), ion mobility spectrometry-derived collision cross section (CCS)—through use of a multimodal, multitask deep learning architecture. Where existing methods require direct generation of information-rich spectra and/or properties, an inherently difficult task, we will simplify molecular signature-based identification by posing the problem as a recognition or retrieval task. The model is thus presented with relevant endpoints – structure and one or more molecular signatures – and need only determine whether they are semantically related. Thus, our approach offers the following advantages over existing techniques: (i) circumvents difficulties associated with direct generation of molecular signatures from structure and structure from signatures; (ii) incorporates multiple molecular signatures simultaneously, as available, to support identification; and (iii) enables rapid computation of structural embeddings toward broad coverage of known chemical space. Taken together, the approach removes the need to explicitly obtain or compute reference spectra, representing a powerful method for compound identification that requires only experimentally observed signatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1988

Novel tether-connected two-dimensional structures for low earth orbits

This paper proposes novel tether-connected two-dimensional structures with a size of several hundred square kilometers for low earth orbits. The attitude of these structures is gravitationally stabilized with respect to an earth-oriented reference frame. A stable shape is obtained by utilizing environmental forces such as differential air drag or electrodynamic forces which stiffen the system. Configurations which differ in geometry and in the number of connecting tethers are presented in the paper. The static stability of each configuration is analyzed as a function of design and orbital parameters. A brief discussion of the applications of such tethered systems is provided at the end of the paper.

Lorenzini, Enrico C.↗
DOE OSTI2026

Cs X Si 15 P 21 ( X = Sn or Pb): Polar Noncentrosymmetric Si–P Frameworks Stabilized by Covalent X –P Bonding

Metal silicon phosphides composed of earth-abundant Si and P tend to exhibit semiconducting properties and adopt diverse crystal structures with relatively small additions of structure-directing elements. The potential of silicon phosphide materials in nonlinear optical applications has been hindered by the inability to systematically produce noncentrosymmetric structures with such a flexible framework. Here, in this work, two isostructural compounds with a novel noncentrosymmetric structure were made possible by the inclusion of elements with stereochemically active lone pairs (Sn 2+ and Pb 2+ ). The structures were determined through single-crystal and synchrotron powder X-ray diffraction. Analysis of chemical bonding in real space through the electron localization function revealed stereochemically active Pb 2+ and Sn 2+ species in a trigonal pyramidal coordination with {Pb/Sn}–P bonds. Such covalent bonding between Pb and P is quite uncommon in extended solids and has been reported in a few rare instances. Band structure calculations and linear optical measurements confirm the semiconducting nature of Cs X Si 15 P 21 ( X = Sn or Pb). The synthesis was optimized to yield high-purity polycrystalline samples. The nonlinear optical properties show promising second-harmonic generation (SHG) coefficients from the Kurtz–Perry method. First-principles calculations of the nonlinear optical properties support the experimentally determined SHG values and provide moderate values of birefringence, suggesting Cs X Si 15 P 21 could be phase-matchable and practical nonlinear optical materials in the mid-IR region.

crystal structure↗
NASA NTRS2022

Quantifying Structural Relationships of Metal-Binding Sites Suggests Origins of Biological Electron Transfer

Biological redox reactions drive planetary biogeochemical cycles. Using a novel, structure-guided sequence analysis of proteins, we explored the patterns of evolution of enzymes responsible for these reactions. Our analysis reveals that the folds that bind transition metal–containing ligands have similar structural geometry and amino acid sequences across the full diversity of proteins. Similarity across folds reflects the availability of key transition metals over geological time and strongly suggests that transition metal–ligand binding had a small number of common peptide origins. We observe that structures central to our similarity network come primarily from oxidoreductases, suggesting that ancestral peptides may have also facilitated electron transfer reactions. Last, our results reveal that the earliest biologically functional peptides were likely available before the assembly of fully functional protein domains over 3.8 billion years ago. Thus, life is a special, very complex form of motion of matter, but this form did not always exist, and it is not separated from inorganic nature by an impassable abyss; rather, it arose from inorganic nature as a new property in the process of evolution of the world. We must study the history of this evolution if we want to solve the problem of the origin of life.

Yana Bromberg↗
DOE OSTI2025

Protein-ligand binding affinity prediction using multi-instance learning with docking structures

Recent advances in 3D structure-based deep learning approaches demonstrate improved accuracy in predicting protein-ligand binding affinity in drug discovery. These methods complement physics-based computational modeling such as molecular docking for virtual high-throughput screening. Despite recent advances and improved predictive performance, most methods in this category primarily rely on utilizing co-crystal complex structures and experimentally measured binding affinities as both input and output data for model training. Nevertheless, co-crystal complex structures are not readily available and the inaccurate predicted structures from molecular docking can degrade the accuracy of the machine learning methods. We introduce a novel structure-based inference method utilizing multiple molecular docking poses for each complex entity. Our proposed method employs multi-instance learning with an attention network to predict binding affinity from a collection of docking poses. We validate our method using multiple datasets, including PDBbind and compounds targeting the main protease of SARS-CoV-2. The results demonstrate that our method leveraging docking poses is competitive with other state-of-the-art inference models that depend on co-crystal structures. This method offers binding affinity prediction without requiring co-crystal structures, thereby increasing its applicability to protein targets lacking such data.

97 MATHEMATICS AND COMPUTING↗